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Udemy - ML from Zero Machine Learning Math & Python from Scratch 2026-9
- Date: 2026-11-10
- Size: 1.1 GB
- Files: 78
File Name
Size
12 - Capstone/65. Benchmark.mp4
35 MB
1 - Introduction/1. What-From-Scratch-Means.mp4
13 MB
1 - Introduction/2. Reading-ML-Math.mp4
12 MB
1 - Introduction/3. Setup.mp4
9.0 MB
1 - Introduction/4. How-to-use-this-course.mp4
9.3 MB
2 - Math-Toolkit/2. The Math Toolkit for ML.html
24 kB
2 - Math-Toolkit/5. Vectors-Dot-Product.mp4
14 MB
2 - Math-Toolkit/6. Matrices.mp4
15 MB
2 - Math-Toolkit/7. Derivatives.mp4
15 MB
2 - Math-Toolkit/8. Gradients.mp4
14 MB
2 - Math-Toolkit/9. Probability.mp4
15 MB
2 - Math-Toolkit/10. Numpy-Vectorization.mp4
15 MB
3 - Linear-Regression/3. Linear Regression from Scratch.html
25 kB
3 - Linear-Regression/11. The-Model.mp4
12 MB
3 - Linear-Regression/12. Cost-Function.mp4
15 MB
3 - Linear-Regression/13. Normal-Equation.mp4
15 MB
3 - Linear-Regression/14. Implementation.mp4
15 MB
3 - Linear-Regression/15. Project-House-Prices.mp4
18 MB
3 - Linear-Regression/16. Metrics-&-Validation.mp4
15 MB
4 - Gradient-Descent/4. Gradient Descent.html
25 kB
4 - Gradient-Descent/17. Why-Iterative.mp4
15 MB
4 - Gradient-Descent/18. Deriving-The-Gradient.mp4
15 MB
4 - Gradient-Descent/19. Learning-Rate.mp4
14 MB
4 - Gradient-Descent/20. Batch-Stochastic-Minibatch.mp4
16 MB
4 - Gradient-Descent/21. Project-Optimize-Regressor.mp4
17 MB
5 - Logistic-Regression/5. Logistic Regression & Classification.html
25 kB
5 - Logistic-Regression/22. Sigmoid.mp4
16 MB
5 - Logistic-Regression/23. Cross-Entropy.mp4
19 MB
5 - Logistic-Regression/24. Log-Loss-Gradient.mp4
15 MB
5 - Logistic-Regression/25. Implementation.mp4
18 MB
5 - Logistic-Regression/26. Project-Breast-Cancer.mp4
17 MB
5 - Logistic-Regression/27. Classification-Metrics.mp4
19 MB
6 - KNN/6. K-Nearest Neighbors.html
25 kB
6 - KNN/28. Distance-Metrics.mp4
17 MB
6 - KNN/29. Implementation.mp4
14 MB
6 - KNN/30. Vectorizing-And-Choosing-K.mp4
16 MB
6 - KNN/31. Project-Wine.mp4
14 MB
7 - Decision-Trees/7. Decision Trees & Random Forests.html
24 kB
7 - Decision-Trees/32. How-Trees-Split.mp4
15 MB
7 - Decision-Trees/33. Entropy-Gini-Gain.mp4
22 MB
7 - Decision-Trees/34. Building-The-Tree.mp4
17 MB
7 - Decision-Trees/35. Overfitting-And-Pruning.mp4
15 MB
7 - Decision-Trees/36. Random-Forest.mp4
17 MB
7 - Decision-Trees/37. Project-Titanic.mp4
17 MB
8 - Naive-Bayes/8. Naive Bayes.html
25 kB
8 - Naive-Bayes/38. Bayes-Theorem.mp4
15 MB
8 - Naive-Bayes/39. The-Naive-Assumption.mp4
15 MB
8 - Naive-Bayes/40. Multinomial-Nb.mp4
15 MB
8 - Naive-Bayes/41. Project-Spam.mp4
18 MB
8 - Naive-Bayes/42. Gaussian-Nb.mp4
18 MB
9 - Kmeans/9. K-Means Clustering.html
25 kB
9 - Kmeans/43. Unsupervised-And-Inertia.mp4
15 MB
9 - Kmeans/44. Lloyds-Algorithm.mp4
15 MB
9 - Kmeans/45. Implementation.mp4
19 MB
9 - Kmeans/46. Choosing-K.mp4
17 MB
9 - Kmeans/47. Project-Segmentation.mp4
29 MB
10 - PCA/10. PCA & Dimensionality Reduction.html
25 kB
10 - PCA/48. Curse-Of-Dimensionality.mp4
17 MB
10 - PCA/49. Covariance-Eigenvectors.mp4
19 MB
10 - PCA/50. Implementation.mp4
15 MB
10 - PCA/51. Explained-Variance.mp4
16 MB
10 - PCA/52. Project-Digits.mp4
17 MB
11 - Neural-Networks/11. Neural Networks from Scratch.html
25 kB
11 - Neural-Networks/53. The-Neuron.mp4
14 MB
11 - Neural-Networks/54. Forward-Propagation.mp4
17 MB
11 - Neural-Networks/55. Activations.mp4
16 MB
11 - Neural-Networks/56. Backpropagation.mp4
20 MB
11 - Neural-Networks/57. Implementation.mp4
17 MB
11 - Neural-Networks/58. Training-Loop.mp4
20 MB
11 - Neural-Networks/59. Project-Mnist.mp4
15 MB
12 - Capstone/12. Capstone & Real-World Workflow.html
25 kB
12 - Capstone/60. The-Workflow.mp4
14 MB
12 - Capstone/61. ProjectA-Eda.mp4
15 MB
12 - Capstone/62. ProjectA-Modeling.mp4
18 MB
12 - Capstone/63. ProjectB-Classifier.mp4
20 MB
12 - Capstone/64. ProjectC-Segmentation.mp4
21 MB
1 - Introduction/1. Introduction, Setup & Reading the Math.html
23 kB
12 - Capstone/66. Where-Next.mp4
21 MB